Article | Open Access
Stuck With the Algorithm: Algorithmic Consciousness and Repertoire in Fridays for Future’s Data Contention
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Abstract: By focusing on the transnational youth climate movement Fridays for Future, this article explores how activists understand algorithms and how they try to use them in their digital campaigns. A qualitative case study, this article provides insights from nine virtual in-depth semi-structured interviews with organizers in social media roles from Fridays for Future country collectives across the globe, giving youth activists the opportunity to tell stories about their understandings and experiences in working in datafied spaces. Four central themes emerge via a three-step qualitative data analysis: algorithmic consciousness (understanding, functions, issues, pitfalls, and misinterpretations), algorithm as stake (contentious importance, tactical politics), algorithm as repertoire (role in activism, algorithmic campaigning), and data contention (data analysis, digital contentious tactics, uncritical uses). The interviews show that activists are stuck with the algorithm in two ways: They have to engage with them but are often unsure how. In that sense, activists frame algorithms as a stakeholder in their campaign but are often unclear on how they work. While organizers recognize algorithmic dependency on campaign success, they lack specific mobilization strategies, which prevents them from leveraging algorithms as a contentious tactic. Data contention includes conducting analytics and tailoring strategies to platforms; yet, datafied spaces are used largely uncritically. This article prompts scholars to go beyond textual analyses of digital activism and conduct research that centers on the experiences and practices of activists in dealing with algorithms and data as structural conditions for digital activism.
Keywords: algorithmic activism; data contention; environmental justice; Fridays for Future; social media mobilization; youth climate activism; virtual interviews
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© Giuliana Sorce. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.